Abstract:
In recent years sensors have been increasingly deployed in the Agricultural fields to monitor the extremely sensitive environmental and climatic changes. Since temperature and humidity are the key factors that affect the growth of crops, temperature sensor, humidity sensor, light sensor and growth sensor are generally plays key role in Agriculture. Expert systems may be used in agricultural field to offer information about the disease management and cure for the crop, soil management, irrigation level to be maintained for the crop, to suggest suitable seed varieties, quantity of fertilizers to be used and finally to find out the expected yield of the crop. Expert systems interact with the farmers and provide solution for the different problems they face in the field from time to time. Semantic web adds structured meaning to the available information and facilitates the machine readability of information. The power of semantic web over traditional web is data re-usability and more relevant accurate search. Agricultural knowledge is so vast and is in unstructured format. Hence it is necessary to incorporate the semantic web for building and processing the knowledge in a structured and disciplined way.
The present paper is aimed at designing and developing a semantic web based wheat expert system with an automatic sensor interface. The system consists of two components namely Information system and Advisory Systems with separate interfaces to both experts and ordinary farmers. The sensor interface is designed using the LM-35 temperature sensor, ADC, 8051 micro controller and MAX 232. Knowledge base is built using ontological structures for the information about the wheat crop with appropriate classes and properties and inference is achieved through SWRL rules. The information system provides the information about wheat varieties, nutrients, diseases, symptoms etc. The user interface takes the average values of temperature and humidity from the observations recorded and calculates the expected yield of the crop using artificial bee colony algorithm.